Feng Jianxing, Liu Tao, Zhang Yong
School of Life Sciences and Technology, Tongji University, Shanghai, China.
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts.
Curr Protoc Bioinformatics. 2011 Jun;Chapter 2:2.14.1-2.14.14. doi: 10.1002/0471250953.bi0214s34.
Model-based Analysis of ChIP-Seq (MACS) is a command-line tool designed by X. Shirley Liu and colleagues to analyze data generated by ChIP-Seq experiments in eukaryotes, especially mammals. MACS can be used to identify transcription factor binding sites and histone modification-enriched regions if the ChIP-Seq data, with or without control samples, are given. This unit describes two basic protocols that provide detailed information on how to use MACS to identify either the binding sites of a transcription factor or the enriched regions of a histone modification with broad peaks. Furthermore, the basic ideas for the MACS algorithm and its appropriate usage are discussed.
基于模型的ChIP-Seq分析(MACS)是由X. Shirley Liu及其同事设计的一款命令行工具,用于分析真核生物(尤其是哺乳动物)ChIP-Seq实验产生的数据。如果提供了ChIP-Seq数据(无论有无对照样本),MACS可用于识别转录因子结合位点和组蛋白修饰富集区域。本单元描述了两个基本方案,提供了关于如何使用MACS来识别转录因子的结合位点或具有宽峰的组蛋白修饰富集区域的详细信息。此外,还讨论了MACS算法的基本思想及其适当用法。